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--- |
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tags: |
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- trl |
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- dpo |
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- generated_from_trainer |
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model-index: |
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- name: tinyllama-chat-mine-dpo |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# tinyllama-chat-mine-dpo |
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This model was trained from scratch on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6240 |
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- Rewards/chosen: -0.7007 |
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- Rewards/rejected: -0.9684 |
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- Rewards/accuracies: 0.6825 |
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- Rewards/margins: 0.2677 |
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- Logps/rejected: -395.3808 |
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- Logps/chosen: -412.6868 |
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- Logits/rejected: -2.7107 |
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- Logits/chosen: -2.7399 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-07 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 4 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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- total_eval_batch_size: 32 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | |
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|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| |
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| 0.6685 | 0.2093 | 100 | 0.6694 | -0.1299 | -0.1943 | 0.6528 | 0.0644 | -317.9682 | -355.6027 | -2.9255 | -2.9507 | |
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| 0.642 | 0.4186 | 200 | 0.6407 | -0.4273 | -0.6175 | 0.6726 | 0.1902 | -360.2873 | -385.3470 | -2.7926 | -2.8208 | |
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| 0.6285 | 0.6279 | 300 | 0.6331 | -0.4723 | -0.6951 | 0.6647 | 0.2228 | -368.0482 | -389.8438 | -2.7731 | -2.8012 | |
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| 0.6222 | 0.8373 | 400 | 0.6240 | -0.7007 | -0.9684 | 0.6825 | 0.2677 | -395.3808 | -412.6868 | -2.7107 | -2.7399 | |
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### Framework versions |
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- Transformers 4.43.3 |
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- Pytorch 2.1.2 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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